1. U-Net with Spatial Pyramid Pooling for Drusen Segmentation in Optical Coherence Tomography

    U-Net with Spatial Pyramid Pooling for Drusen Segmentation in Optical Coherence Tomography

    The presence of drusen is the main hallmark of early/intermediate age-related macular degeneration (AMD). Therefore, automated drusen segmentation is an important step in image-guided management of AMD. There are two common approaches to drusen segmentation. In the first, the drusen are segmented directly as a binary classification task. In the second approach, the surrounding retinal layers (outer boundary retinal pigment epithelium (OBRPE) and Bruch’s membrane (BM)) are segmented and the remaining space between these two layers is extracted as drusen. In this work, we extend the standard U-Net architecture with spatial pyramid pooling components to introduce global feature ...

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